{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Python基础教学代码---高阶篇  \n",
    "1.面向过程编程  \n",
    "2.面向对象编程   \n",
    "3.正则表达式  \n",
    "4.线程与进程  \n",
    "5.总结\n",
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1.面向过程编程  \n",
    "定义方法指令:def  \n",
    "\n",
    "面向过程编程是通过定义一个又一个的方法去确定的，在数学上我们更倾向于将方法称作函数。  \n",
    "这么做的目的是为了将一个大的任务拆成一个又一个小任务去实现，然后用搭积木似的操作去组装，  \n",
    "从而完成任务。\n",
    "\n",
    "我们可以将积木看做方法，这些方法都是我们实现的，将一个又一个的积木组装成自己想要的形状，就是完成任务的过程。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 有返回值,无参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def print_value():\n",
    "    return 1\n",
    "print_value()  # 调用函数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 无返回值,无参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chile\n"
     ]
    }
   ],
   "source": [
    "def print_value():\n",
    "    print('Chile')\n",
    "print_value()  # 调用函数    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 无返回值,有参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a < b\n",
      "a < b\n",
      "a < b\n"
     ]
    }
   ],
   "source": [
    "def print_value(a, b):\n",
    "    if a > b:\n",
    "        print('a > b')\n",
    "    elif a < b:\n",
    "        print('a < b')\n",
    "    else:\n",
    "        print('a == b')\n",
    "        \n",
    "# 三种调用方式        \n",
    "print_value(1, 2)  # 调用函数  \n",
    "\n",
    "a = 1\n",
    "b = 2\n",
    "print_value(a, b)  # 调用函数  \n",
    "\n",
    "print_value(a=1, b=2)  # 调用函数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 有返回值,有参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a < b\n",
      "a < b\n",
      "a < b\n"
     ]
    }
   ],
   "source": [
    "def print_value(a_test, b_test):\n",
    "    if a > b:\n",
    "        return 'a > b'\n",
    "    elif a < b:\n",
    "        return 'a < b'\n",
    "    else:\n",
    "        return 'a == b'\n",
    "        \n",
    "# 三种调用方式        \n",
    "print(print_value(1, 2))  # 调用函数  \n",
    "\n",
    "a = 1\n",
    "b = 2\n",
    "print(print_value(a, b))  # 调用函数  \n",
    "\n",
    "print(print_value(a_test=1, b_test=2))  # 调用函数 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2.面向对象编程\n",
    "面向对象有两个概念:类（Class）和实例（Instance），  \n",
    "类是抽象的模板，比如Phone类，而实例是根据类创建出来的一个个具体的“对象”比如huawei、iphone等，  \n",
    "每个实例的对象都拥有相同的方法，但各自的数据可能不同。 \n",
    "\n",
    "每一个方法第一个参数永远是self。  \n",
    "类的三大特性：封装、继承与多态\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 封装  \n",
    "将属性和方法封装进类，每一个对象的属性和方法是一样的，类似模板，  \n",
    "但数据不一样，类似我们将自己的内容输入模板。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Phone(object):\n",
    "    # 内置的方法，用来绑定类的属性\n",
    "    def __init__(self, name, price):\n",
    "        # 属性\n",
    "        self.name = name  \n",
    "        self.price = price\n",
    "    \n",
    "    # 方法\n",
    "    def print_price(self):\n",
    "        print(self.price)\n",
    "    def assistant(self):\n",
    "        print('I have an assistant!')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 实例化对象"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5200\n",
      "8888\n"
     ]
    }
   ],
   "source": [
    "iphone = Phone('iphone', 5200)\n",
    "huawei = Phone(name='huawei', price=8888)\n",
    "print(iphone.price)  # 查看实例属性\n",
    "huawei.print_price()  # 调用实例函数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 继承\n",
    "就是传统意义上的意思，继承父辈已有的东西，然后在自己身上开发父辈没有的东西。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Iphone(Phone):\n",
    "    def operation_system(self):\n",
    "        return 'ios'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ios\n"
     ]
    }
   ],
   "source": [
    "iphone = Iphone('iphone', '5200')\n",
    "print(iphone.operation_system())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 多态  \n",
    "如果从父辈继承的方法不适合，子类会重写一个适合自己的同名方法，覆盖从父辈那继承的已有的方法。  \n",
    "即在运行子类的实例时，总是优先运行子类的代码。  \n",
    "所以多态也叫多样性。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Iphone(Phone):\n",
    "    def assistant(self):\n",
    "        print('I have siri assistant!')\n",
    "\n",
    "class Huawei(Phone):\n",
    "    def assistant(self):\n",
    "        print('I have hormony assistant!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I have siri assistant!\n",
      "I have hormony assistant!\n"
     ]
    }
   ],
   "source": [
    "iphone = Iphone('iphone', 5200)\n",
    "huawei = Huawei(name='huawei', price=8888)\n",
    "iphone.assistant()\n",
    "huawei.assistant()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_assistant(Phone):\n",
    "    Phone.assistant()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I have an assistant!\n",
      "I have siri assistant!\n",
      "I have hormony assistant!\n"
     ]
    }
   ],
   "source": [
    "get_assistant(Phone('phone', 500))\n",
    "get_assistant(Iphone('iphone', 5200))\n",
    "get_assistant(Huawei('huawei', 8888))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 面向过程与面向对象的区别\n",
    "面向过程的程序设计是以过程为中心，将问题分解成一个个小问题，然后用一个个函数将这些小问题  \n",
    "按照步骤去解决，即把大函数切成小函数，从而降低问题的复杂度。    \n",
    "\n",
    "而面向对象的程序设计是以对象为中心，将事物高度抽象化成模型，然后使用模型实例化出一个个对象，  \n",
    "通过对象之间的通信来解决问题。\n",
    "  \n",
    "\n",
    "不管是面向过程还是面向对象编程，本质上都是为了简化代码，提高代码复用率，只不过面向对象更加抽象罢了。\n",
    "\n",
    "越抽象的东西，通用性越高，当然也就意味着复用性越好。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3.正则表达式  \n",
    "正则表达式是一个特殊的字符序列，帮助我们匹配我们想要的字符串格式。  \n",
    "参考链接：https://www.runoob.com/python/python-reg-expressions.html"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## re.match  匹配字符串开头，开头不匹配直接返回None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0, 5)\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "#!/usr/bin/python\n",
    "# -*- coding: UTF-8 -*- \n",
    " \n",
    "import re\n",
    "print(re.match('Chile', 'ChileWang').span())  # 在起始位置匹配\n",
    "print(re.match('Wang', 'ChileWang'))         # 不在起始位置匹配"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## re.search 返回字符串中第一个匹配的匹配  \n",
    "re.search(pattern, string, flags=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0, 5)\n",
      "<re.Match object; span=(5, 9), match='Wang'>\n"
     ]
    }
   ],
   "source": [
    "import re\n",
    "print(re.search('Chile', 'ChileWang').span())  # 在起始位置匹配\n",
    "print(re.search('Wang', 'ChileWang'))         # 不在起始位置匹配"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## re.sub 替换字符串中的匹配项"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "re.sub(pattern, repl, string, count=0, flags=0)  \n",
    "参数：  \n",
    "pattern : 正则中的模式字符串。  \n",
    "repl : 替换的字符串，也可为一个函数。  \n",
    "string : 要被查找替换的原始字符串。  \n",
    "count : 模式匹配后替换的最大次数，默认 0 表示替换所有的匹配。  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "QQ邮箱是:  1234567@qq.com \n",
      "163邮箱是:  1234567@163.com\n"
     ]
    }
   ],
   "source": [
    "#!/usr/bin/python\n",
    "# -*- coding: UTF-8 -*-\n",
    " \n",
    "import re\n",
    " \n",
    "phone = \"1234567@qq.com # 这是一个QQ邮箱\"\n",
    " \n",
    "# 删除字符串中的 Python注释 \n",
    "num = re.sub(r'#.*$', \"\", phone)\n",
    "print (\"QQ邮箱是: \", num)\n",
    " \n",
    "# 用@163.com替换非数字(@qq.com)的字符串 \n",
    "num = re.sub(r'\\D+', \"@163.com\", phone)\n",
    "print (\"163邮箱是: \", num)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## re.compile 函数\n",
    "compile 函数用于编译正则表达式，生成一个正则表达式（ Pattern ）对象，供 match() 和 search() 这两个函数使用。 \n",
    "## findall\n",
    "在字符串中找到正则表达式所匹配的所有子串，并返回一个列表，如果没有找到匹配的，则返回空列表。 \n",
    "\n",
    "findall(string, pos, endpos)  \n",
    "参数：  \n",
    "string : 待匹配的字符串。  \n",
    "pos : 可选参数，指定字符串的起始位置，默认为 0。  \n",
    "endpos : 可选参数，指定字符串的结束位置，默认为字符串的长度。  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['111', '222']\n",
      "['111', '444']\n"
     ]
    }
   ],
   "source": [
    "# -*- coding:UTF8 -*-\n",
    " \n",
    "import re\n",
    " \n",
    "pattern = re.compile(r'\\d+')   # 查找数字\n",
    "result1 = pattern.findall('Chile 111 Wang 222')\n",
    "result2 = pattern.findall('Chi111le444Wang333', 0, 11)\n",
    " \n",
    "print(result1)\n",
    "print(result2)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## *正则表达式的重点\n",
    "\n",
    "正则表达式的核心是如何构建一个正则对象去匹配我们需要的字符，这里涉及到很多的正则符号，  \n",
    "之前的代码只是简单的介绍了匹配（'\\d+'）数字或者（'\\D+'）非数字，其实还有很多很多的匹配项，如下图。  \n",
    "这是一个庞大的知识体系，我们不可能完全记住，也不可能完全精通，因此我们只需要在使用的时候翻阅一下即可。    \n",
    "\n",
    "目前，互联网上已经有很多正则表达式的匹配教程，博主在此提及它，只是想让初学的小伙伴  \n",
    "知道有这么一个东西，等到需要用的时候，通过互联网去查阅即可。\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4.进程与线程  \n",
    "截至到现在，大家写的代码都是完成单任务的，那如果我们想让Python同时进行多个任务呢？这就涉及到了进程和线程。  \n",
    "这里博主先科普一波啥是进程与线程。  \n",
    "\n",
    "举个例子，我们在电脑上可以同时运行QQ和微信等多个软件，这些软件就是在一个个进程中运行的。而我们在QQ上即可以聊天也可以看新闻，这就是  \n",
    "进程里面一个个线程所做的事。  \n",
    "\n",
    "因此，一个进程中至少拥有一个线程。\n",
    "\n",
    "不过多线程和多进程一样，是统一由操作系统在线程中快速切换，切换速度比人类肉眼可见速度快，造成好像多个任务同时运行的假象。  \n",
    "但是如果我们的操作系统拥有多个CPU，就可以让多任务同时进行，可以让每个CPU都运行一个进程即可。\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 多进程例子  \n",
    "进程池Pool，这里博主用进程池举例，进程池的默认参数是CPU核数目。  \n",
    "当然啦，互联网上也有很多别的多进程使用方法，思想都是一样的，只是实现方式不同，小伙伴们可以选择  \n",
    "自己喜欢的方式。  \n",
    "\n",
    "参数设置成4，代表同时进行4个进程，第5个进程要等前面4个进程中的某个进程结束才能开始执行。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "执行任务 0 ...\n",
      "执行任务 1 ...\n",
      "执行任务 2 ...\n",
      "执行任务 3 ...\n",
      "任务 1 执行时间： 0.67 s.\n",
      "执行任务 4 ...\n",
      "任务 3 执行时间： 2.45 s.\n",
      "任务 2 执行时间： 2.78 s.\n",
      "任务 0 执行时间： 3.29 s.\n",
      "任务 4 执行时间： 3.49 s.\n",
      "所有进程完成！\n"
     ]
    }
   ],
   "source": [
    "from multiprocessing import Pool\n",
    "import time, random\n",
    "\n",
    "def random_time_task(name):\n",
    "    print('执行任务 %s ...' % (name))\n",
    "    start_time= time.time()\n",
    "    time.sleep(random.random() * 5)\n",
    "    end_time = time.time()\n",
    "    print('任务 %s 执行时间： %0.2f s.' % (name, (end_time - start_time)))\n",
    "\n",
    "if __name__=='__main__':\n",
    "    p = Pool(4)\n",
    "    for i in range(5):\n",
    "        p.apply_async(random_time_task, args=(i,))\n",
    "    p.close()  # 调用close保证所有进程结束后，不再进入新的进程\n",
    "    p.join()\n",
    "    print('所有进程完成！')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 多线程例子   \n",
    "线程和进程之间还是存在一定区别的，每一个进程的变量都是独一无二的，类似QQ和微博，两者独立运行互不影响。但是同一个进程内的线程  \n",
    "是共享同一套变量的，类似我们同时取钱，第一个线程取完了所有的钱，第二个线程就不能再取钱了，因为已经没钱了。  \n",
    "因此，为了避免我们程序出现Bug，我们需要引入Lock锁机制，保证线程间在操作过程中，不能同时对同一变量进行操作。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10\n"
     ]
    }
   ],
   "source": [
    "import threading\n",
    "balance = 10  # 银行余额\n",
    "lock = threading.Lock()\n",
    "\n",
    "def operation2balance(money): \n",
    "    global balance  # 全局变量\n",
    "    balance = balance + money  \n",
    "    balance = balance - money\n",
    "\n",
    "def new_thread(n):\n",
    "    for i in range(20):\n",
    "        # 操作前先获得锁\n",
    "        lock.acquire()\n",
    "        try:\n",
    "            operation2balance(n)\n",
    "        finally:\n",
    "            # 操作后释放锁\n",
    "            lock.release()\n",
    "\n",
    "# 启动两个线程\n",
    "t1 = threading.Thread(target=new_thread, args=(29,))\n",
    "t2 = threading.Thread(target=new_thread, args=(18,))\n",
    "t1.start()\n",
    "t2.start()\n",
    "t1.join()\n",
    "t2.join()\n",
    "print(balance)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
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    "# 5.总结  \n",
    "![image.png](attachment:image.png)  \n",
    "\n",
    "代码链接：https://github.com/ChileWang0228/DeepLearningTutorial/tree/master/Python_Basis  \n",
    "\n",
    "当然，Python能做的事不止这些，我们可以用Python写网页后台，也可以用它来操作数据库等等。所以有些小伙伴可能会    \n",
    "疑惑为啥博主没有给大家把Python的更多细节说清楚。在这里博主首先声明不是偷懒，原因有四，待我细细诉说。  \n",
    "  \n",
    "️1.目前阶段的编程学习已经能完全应付这个系列的课程了，没有必要深入把目前用不着的知识给大家灌输一遍，没有实战，  \n",
    "灌输再多边边角角的知识也只是走马观花，很难融会贯通。  \n",
    "  \n",
    "️2.博主已经帮助大家建立好了Python最基本知识体系，它犹如大树的枝干，而其他的知识犹如枝叶，枝叶会在这颗枝干下不断衍生。  \n",
    "那么衍生枝叶所需要的养分呢？那就是你接下来碰到的一个个需要解决的项目，我们在掌握最基本的知识的情况下，  \n",
    "通过实战去磨砺我们对所学知识的运用，最终量变决定质变。  \n",
    "  \n",
    "️3.网上的知识已经过于冗余，博主要给大家做减法，而建立一个知识体系就是给大家做减法。   \n",
    "有时候我们只需要知道某个东西能解决哪些问题，比如pandas或者numpy这两个包可以解决很多很多的问题，  \n",
    "但是你目前用不着，讲再多也是徒劳，不过我们知道它们的强大，那就在我们需要它们的时候，利用互联网去搜索即可，  \n",
    "互联网上总会有人碰到和你一样的问题，并有人已经提供了答案。  \n",
    "  \n",
    "️4.一切的项目都是从最基本的语法出发的，它们是万丈高楼的基石，我们想砌什么样的楼房不是看砖头长什么样，而是看设计图长什么样。  \n",
    "同样的砖头在不同的图纸下，就会砌出不同的形状的楼房。同样的语法，在不同的学习路线下，就细分出不同的专业领域。  \n",
    "此时，我们回到最开始的问题，Python确实可以做很多的事，但是都是从最基本的知识点出发，   \n",
    "至于接下来小伙伴们是想从事数据挖掘，还是人工智能，亦或者是网页开发，甚至是爬虫工程师，  \n",
    "那就看大家接下来的学习路线了。现在互联网上有很多学习资源，大家一定要学会使用搜索引擎，遇事不决先搜索，  \n",
    "这也是锻炼自己的学习能力。学会规划学习路线和善用搜索引擎才是成长的关键所在。  \n",
    "  \n",
    "最后，我们要始终铭记，编程只是工具，并不需要很聪明的脑瓜子，也不需要太多的奇技淫巧，无他，唯熟尔。  \n",
    "上诉所说不仅仅适用于编程的学习，也是我们应对当下互联网信息大爆炸时代下的有效学习途径。  \n"
   ]
  }
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